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Financial Deepening and Economic Growth in Indonesia


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Berkala Kajian Ekonomi dan Studi Pembangunan


Financial Deepening And Economic Growth In Indonesia

Wasiaturrahma1*, Ramses Muhammad Rizal2 , Shochrul Rohmatul Ajija3 1,2,3 Economics Department, Faculty of Economics and Business, Airlangga University


Informasi Artikel

The purpose of this study is to analyze the impact of financial deepening on economic growth in Indonesia. The time period studied for this research is from 1975 until2016. This study uses a quantitative research approach in the form of statistics and econometrics regression data. The data used is based on the annual time series data from 1975 until 2016. In this research, two models of testing are used, namely ARDL (Autoregressive Distributed Lag) and ECM (Error Correction Model). The results of this study indicate that financial deepening has a significant negative impact on economic growth in Indonesia. The Broad Money, Government Expenditure and Trade Openness variables influenced the variables of economic growth simultaneously in the period 1975-2016, but only the GDP and Trade openness variables had a significant influence on the dependent variable of GDP during the researched period. Therefore, Bank Indonesia (BI) needs to conduct further research on Broad Money trading (M2) so that the function of economic depth can encourage the growth of GDP Indonesia. In addition, there is a need for policies that will stimulate and facilitate foreign and domestic companies to sell their shares on BEI (Indonesian stock exchange) so that they can be traded by people whose impact will increase Indonesia’s economic growth.

Sejarah artikel: Diterima November 2018 Disetujui November 2018 Dipublikasikan Maret 2019 Keywords: Financial Deepening, Monetary Economics, Economic Growth

© 2019 MediaTrend

Penulis korespondensi: E-mail: rachma1904@gmail.com DOI: http://dx.doi.org/10.21107/mediatrend.v14i1.4552 2460-7649 © 2019 MediaTrend. All rights reserved.



The role of the financial system is

that of a financial intermediary in the eco

-nomic system that serves to facilitate tran-sactions between individuals or institutions that have excess funds and parties who need funds. If this function does not run well, economic growth will be affected. In Indonesia, the role of financial

intermedi-aries is mostly limited to saving and bor

-rowing funds. There is only a small per

-centage of people who understand about the capital market and stock exchange trading of Indonesia (BEI).

Financial markets have a role as financial intermediaries, namely, providing capital to various investment products to

investors so as to create economic stabili

-ty. This results in an increase in the stability of the accumulation of personal wealth and in the economy. Unused funds will hamper economic growth in Indonesia if it is not maximally utilized. In addition, the lack of information on banking products such as

bonds and stocks will cause low participa

-tion of the public who have excess funds to participate in the financial market. This

causes Bank Indonesia to be less than op

-timal in using excess funds in the commu

-nity so that if there is an economic shock it will be difficult or slow to restore it.

By the end of the twentieth century, the governments of industrialized countries

had almost eliminated most, if not all, poli

-cies that hindered the cross-border move

-ment of financial capital. He believes that economic liberalization provides benefits to a country. This is because free capital

mobility is believed to provide an opportu

-nity to realize the highest return from sa-vings, loans at the most competitive rates, and diversification of country-specific risks. This liberalization will then result in

deve-lopment finance which is the main compo

-nent of economic growth (Klein and Olivei, 2005).

In the context of financial liberaliza

-tion that many developing countries have

taken steps to increase financial freedom

through the creation of their financial sys

-tems more as a tool for economic growth (Klein and Olivei, 2005). In the financial sector, financial intermediaries, such as banks, insurance companies, and capital markets mobilize funds from surplus units to those who do not have funds (Arizala, Cavallo and Galindo, 2009).

Financial markets play an impor

-tant role in terms of sustaining economic growth, they support by channeling capital

into various investment products giving in

-vestors an opportunity to stabilize the ac

-cumulation of personal wealth and add to

the overall stability of the economy by di

-versifying sources of funding. This is where the role of economic deepening (Financial Deepening) comes in to provide a wide range of investment products for investors in order to create economic stability.

Financial deepening is a concept that can be understood in three ways. First, the banking sector and banking agents can use the various financial markets for

sa vings and investment decisions, includ

-ing on long maturities. Secondly, finan

-cial and market intermediaries can deploy

larger volumes of capital and greater turn

-over, without requiring large movements to match asset prices that occurs in the liquid market (Chami, et al., 2009). The third way is the ability of the financial sector to make broad asset choices in risk sharing, which

is essential in order to provide an oppor

-tunity to protect the Indonesian Rupiah against foreign currencies by diversifying financial products. Deep financial markets enable investments in high-quality assets

and risk-sharing instruments. A deep fi

-nancial market also allows borrowers to equally absorb various financing and risk management instruments (Goswami and Sharma, 2011).

In many empirical studies,

cross-country research shows a positive rela

-tionship between financial deepening and economic growth. This indicates that the


initial level of financial development is a good predictor of the next level of econo-mic growth (Levine and King, 1993). Other studies alternatively present evidence of

the negative effects of financial deepen

-ing on growth (De Gregorio and Guidotti, 1995). However, cross-country research fails to address specific macroeconomic environmental states leading to biased

policy implications. Therefore, it is very im

-portant to investigate the effects of finan

-cial deepening on economic growth based on state cases.

This study is based on previous re

-search conducted by Hazem and Husam (2014), but this study has differences with the previous research. The key difference lies in the sample and period of years used. In this study the samples and periods used are from the year 1975 to 2016, while the research conducted by Hazem and Husam (2014) used a sample of Saudi Arabia from the period 1970-2010. Since there was still the lack of previous studies regarding

financial deepening in Indonesia, the pur

-pose of this study is to pinpoint the influ

-ence of financial deepening on economic growth in Indonesia in the period 1975-2016.


Khasmir (2002) argues that the fi

-nancial system serves to channel funds

from lenders / savers to borrowers / spend

-ers to finance productive activities. Funds can be disbursed from the owner of the surplus funds to the borrower (deficit unit) in three ways: (1) Direct financing in the form of direct lending is done by the owner of surplus funds to the borrower (deficit

unit) without involving any financial inter

-mediary institution. For example, the de

-livery of evidence of debt, such as bonds, shares, or promos to the unit that lends. (2) semi-direct financing through the process of channeling of funds lent from a surplus unit to a deficit unit using an individual or institutional intermediary. Financing can be

done with two methods, i.e., through an in

-vestment bank or broker. (3) Indirect Fund

-ing is the process of transferr-ing loan funds from units experiencing a surplus to units

experiencing deficits through financial in

-termediary institutions such as banks,

insurance companies, pension funds, se

-curities financing and mutual funds. Use of intermediary institutions is important in the economy because it can overcome the weaknesses that exist in direct financing.

McKinnon (1973) and Shaw (1973)

argue that in developing countries, espe

-cially when interest rates are liberalized, it will lead to an increase in real interest rates that will lead to an increase in savings ,

spur investment and ultimately boost eco

-nomic growth. The initial framework of

McKinnon (1973) and Shaw (1973) focus

-es on financial suppr-ession and the need to ease financial pressures by allowing markets to determine rates, elimination of credit controls among others. The results of the persecution, according to McKinnon (1973) and Shaw (1973) will lower savings, increase consumption, lower investment and lead to depressed economic growth. The McKinnon-Shaw framework centers on market distortions caused by financial pressures (Savanhu et al., 2011).

In the view of Rajan and Zingales

(2003), financial development creates con

-ditions that allow for growth through the sector of excellence growth or demand

(following the growth in demand for finan

-cial products). A large empirical research supports the view that the development

of the financial system contributes to eco

-nomic growth (Rajan and Zingales, 2003).

The empirical evidence consistently em

-phasizes the relationship between finance and growth, although the issue of causality is more difficult to determine. At the

cross-country level, evidence suggests that vari

-ous measures of financial development (in

-cluding financial intermediary assets, liquid financial liabilities, domestic credit to the private sector, stock market capitalization


and bonds) are strongly and positively as

-sociated with economic growth (King and Levine, 1993; Levine and Zervos, 1998).

Economic growth is the develop

-ment of activities in an economy that cause

goods and services produced in the com

-munity to increase so that the prosperity of society also increases (Sukirno, 2010). The ability of a country to produce goods and services will increase due to the increase of production factors both in quantity and quality. In this fashion, economic growth can serve as a benchmark achievement of the development of an economy from one period to another. Economic growth is always expressed as a percentage; this is because the percentage is a calculation of the change in national income in a certain

time period when compared with the previ

-ous period.


This study uses a quantitative ap

-proach that combines hypothesis testing with measured data so the influence of each variable will be known against other variables and will produce a conclusion. This study uses secondary data in the form of time series data starting from 1975 until 2016.

This study uses two models of test

-ing, namely ARDL (Autoregressive Distri-buted Lag) and ECM (Error Correction Model). Autoregressive Distributed Lag

(ARDL) is a technical co-integration ap

-proach or a Bound test of co-integration which has been the solution in determining long-term relationships with non-stationary data. The Autoregressive Distributed Lag

test is used to understand long-term rela

-tionships with non-stationary data, includ

-ing newly developed ARDL Pesaran and Shin (1995, 1998), Pesaran et al. (1996), Pesaran (1997) and Pesaran et al. (2001). The ARDL test was chosen because the results were stronger for smaller samples unlike conventional approaches such as Engledan Granger (1987), Johansen

(1988) and Gregory and Hansen (1996) which are more suitable for large size samples. Then, the Error Correction Model (ECM) is a model approach that combines ARDL with ECM to determine the short-term dynamic relationship to the variables being studied (Pesaran and Shin (1999) and Pesaran et al. (2001)). ECM has a

long-term equilibrium and uses it as an ex

-planatory variable in the dynamic proper

-ties of the previous variable (Tsay, 2002). Based on the hypothesis that has

been drawn the technique chosen to per

-form the regression is ARDL (Autoregres

-sive Distributed Lag) to determine the long-term and ECM (Error Correction Model) to find the short term.

1. ARDL Model

2. ECM Model

Where α1 is long-term constants, α2 is

Short-term constants, lnGDP is Log GDP, lnM2 is M2, lnGOV is Log Government expenditures, lnTO is Log Trade Openness,

elt is Error term

The statistical analysis in this re-search is based on t-statistic test, f-statistic test, and coefficient determinant test (R2). The t-statistic test is a model test to determine the effect of independent variables (X) on the dependent variable (Y). Testing of t test criteria is if t test value> t critical then H0 is rejected which means the independent variable (X) influences the dependent variable (Y). The F-Statistic Test is a model test to determine whether or not an independent variable influences the dependent variable simultaneously.


Testing the hypothesis of F-Statistic can use p-value, that is the compared value from p-value from F with F table (Critical value). If the value of probability (p-value) is smaller than the level of significance α (1%, 5%, 10%) then it can be said that the independent variable has a significant influence on the dependent variable. Testing R2 has a function to determine whether variations of the independent variables can explain the variations of the variables in an estimation model well. R2 value ranges from 0 to 1. If the value of a coefficient of determination (R2) is equal to or close to 1, it means that the independent variable can explain the dependent variable well. Conversely, if the value of R2 is equal to or close to the number 0 if gives the sense that the independent variable can’t explain the dependent variable well.


Trade openness is the highest level of growth and the opening of a country’s trade will increase the economic growth which will eventually increase GDP growth. In addition, the growth of M2 broad money will increase. Growth from year to year is driven by trade openness due to the increasingly open trade of Indonesia. GDP growth is quite volatile because apart from being affected by trade openness, GDP growth is also affected by government expenditures or government spending. In 1983, when trade openness increased, it

also caused GDP growth to increase due to the increasing number of trade activities with other countries and the entry of investors into Indonesia which contributed to the GDP growth in 1983. Although it decreased in 1993, in the following years experienced an increase again because in 1993 Indonesia experienced an economic boom that resulted in increased incomes of society, thus increasing the money supply. In addition, the increasing variety of banking products also contributed to the increase in the money supply (M2).

In this study, the author aims to determine the effect of Broad Money, Go-vernment expenditure, and Trade Openness on GDP growth with the analysis tool known as Autoregressive Distributed Lag (ARDL). Based on estimation techniques, panel data regression models can be estimated using two estimation methods, namely Au-toregressive Distributed Lag (ARDL) and Error Correction Model (ECM),

Based on the data in the table above the regression results using ARDL (Autoregressive Distributed Lag) AIC (Akaike Information Criterion) we can conclude that broad money has a pro-bability of more than 0.05 is 1.00 then the broad money as a whole does not affect the economic growth in the long term. Other variables are Government expenditures which have a probability of exceeding the level of trust (α = 0.05). Government expenditure variables tend

Tabel 1


not to affect economic growth and tend not to cause fluctuation in the rate of growth or decline. In table 1.1 above, Government expenditures have a probability level of 0.108 which in the long run does not affect the economic growth. Independent variables that significantly affect the dependent variables are GDP and trade openness, because GDP has a probability of 0.0003 which can be interpreted as 1% which can affect the dependent variable. Trade openness has a probability of 0.011 which can also be interpreted to affect the dependent variable by 5% in the long run.

The result of ECM (Error Correction

Model) model shows only the Trade Open

-ness variable has a significantly positive

effect and shows to have significant im

-pact on economic growth. While the Broad

Money variable and Government expendi

-ture in the short term cannot affect the de

-pendent variable of economic growth. The Broad Money (M2) variable has a proba-bility of 0.41 which exceeds the trust level (α = 0.05) so it can be interpreted that the variable does not affect economic growth

in the short term, while the government ex

-penditures variable in the short term also does not affect economic growth because

it has a probability level of 0.107 that ex

-ceeds the confidence level (α = 0.05). Based on the result of the ARDL regression, the obtained value of probabi-lity statistic F equals to 0.000 which means that the probability value is smaller than

the level of trust (α) 0,05 so from the result of the regression variable for Broad Money,

Government expenditure and Trade Open

-ness can influence the variable of GDP to



This study aims to determine the

effect of Broad Money, Government ex

-penditure, and Trade Openness on GDP in the period from 1975-2016. Broad Money in real terms can be used as an indicator of the amount of time deposit trading activities,

money market deposits, stocks, and other forms of money that can be found easily

and at a low cost. Government expendi

-tures are the total purchases made by the government on goods and services that cannot be provided by the private sector,

including public consumption, public in

-vestment and transfer payments compris

-ing pension benefits and social benefits.

Trade Openness is the level of trade open

-ness of a country with other countries, with the opening of trade a country will be able to upgrade technology controlled by other

countries which in turn increases the over

-all level of technology and will decrease

the cost of production of the country’s ex

-ported goods, which ultimately improves the country’s economy.

Trade openness has a big influ

-ence on the growth of GDP and the greater the amount of the open trade activity, the

Tabel 2


greater will be the increase in GDP, be

-cause the probability of Trade openness is

0.011 i.e. low level of trust α = 0.05. There

-fore, the economy is more open, but still needs to maintain supervision of imported products in order to protect the domestic products.

Broad money (M2) is a bench

-mark for GDP because there are still some traders , the stock market, and other forms of money that can be found easily and at a low cost. Broad Money Variable (M2) in the Long run has a significant influence on GDP. This exceeds trust level α = 0.05. This can be attributed to the public know-ledge of banking products other than sa-vings and loans. So BI needs to provide education about the trading of time depo-sits, money market deposits and stocks, so that more people who do trading can make use of time deposits or stocks.

Another variable is Government expenditures (GOV), and this study shows

that the variable of Government expendi

-tures is not significant at all to GDP. This Government expenditures variable does not appear to be related to other variables such as broad money (M2) and trade

openness. The patterns of government ex

-penditures tend to be flat or do not have a fluctuating rise and decline and tend to be stable. This is indicated by the 0.108 pro-bability value of Government expenditures (GOV) which exceeds the trust level of α = 0.05.

The relationship between financial deepening and long-term economic growth is surprisingly negative. Nevertheless, in

the short term, there is no significant im

-pact of financial deepening to economic growth. In addition, long-term Growth and

Trade Openness GDP variables show sig

-nificant influence, but in the short term only

Trade Openness variables show signifi

-cant influence this is because in the short-term financial deepening has no impact on economic growth.

The relationship between financial

deepening has a negative effect on eco

-nomic growth. Any increase in financial deepening of 1.00 will not lead to econo-mic growth. This shows that the financial depth measured using M2 will not lead to economic growth in Indonesia. However, in previous studies other countries showed different results, such as the financial depth measured using M2 would lead to economic growth.


Based on the results of the research and discussion in the previous chapters, the conclusions obtained in this study are

that the variables Broad Money, Govern

-ment Expenditure and Trade Openness have all had an effect on the variables of economic growth in the period 1975-2016. However, only the GDP variables and Trade openness had a significant influence on the dependent variable of GDP in the

period 1975-2016. Broad Money, Govern

-ment Expenditure, and Trade Openness

variables partially affected the GDP vari

-ables in the period 1975-2016. Variable Trade Openness had a significant effect on the variable of GDP both in the short term and long term in the period 1975-2016.

Therefore, Bank Indonesia (BI) needs to conduct further research on

Broad Money trading (M2) so that the func

-tion of economic depth can encourage the growth of Indonesia’s GDP. Concurrently, stock trading transactions of both foreign

and domestic companies need to be im

-proved and the owners of the companies should be encouraged to go public so their shares can be traded in the stock market. Furthermore, policies that would stimulate

and facilitate foreign and domestic compa

-nies to sell their shares on BEI (Indonesian stock exchange) should be made so that the shares can be traded by the people whose impact will increase the economic growth of Indonesia.



The limitations of this study are the

lack of previous research on financial deep

-ening in Indonesia. Research on financial deepening in Indonesia is not easy to do and takes a long time. This may result in

the lack of financial deepening implemen

-tation in Indonesia so that the benefits of financial deepening will be less perceived and will cause Indonesia to face difficulty in finding sufficient foreign capital to achieve economic growth in the future and result in

slowing growth of the financial markets. In

-donesia will find it difficult to withstand eco

-nomic shocks if they happen and will be slow in its recovery. In addition, there was an absence of variables significant to the research on financial deepening so it was difficult to choose what variables will be significant to financial deepening research.


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